The current, highly competitive, semiconductor market is forcing semiconductor companies to remain competitive in terms of productivity and time to market. Competitive semiconductor manufacturing companies focus on reducing manufacturing time while maintaining or increasing production output. Reducing manufacturing time is accomplished by reducing Work In Process (“WIP”) inventory so that manufacturing time is reduced but production output is not decreased. Manufacturing time will also be reduced when variation in the production line is reduced. The less variation in the production line, the shorter that cycle time can be made.
Minimzing WIP inventory and reducing manufacturing time are usually accomplished by efficient scheduling and dispatching of lots to be processed so as to reduce the amount of time each lot waits at a particular station. One known scheduling and dispatching solution is to use simulation techniques. Simulation based scheduling provides the benefit of testing the scheduling rules in the simulation environment before the scheduling rules are implemented. Simulation based scheduling also provides an integrated system between simulation and the scheduler functions in order to timely evaluate and implement scheduling rules and scheduling parameter changes.
A weakness found in many prior art simulation projects is the obsolescence of data used by the simulation model. Wafer fabrication, for example, involves complex dynamic production systems. The measurement of their capacity and performance such as lead time and wafer output are not accurate enough if a solution capable of modeling the dynamic fabrication conditions and variance in the system is not used. The main problem is that building a complete fabrication simulation model manually is a daunting task that requires many hours and coordination between many personnel to finish the task timely before the model, i.e., logic and data, become obsolete. Also of note is that the maintenance of the simulation models is complex and expensive.
Traditional system integration efforts have focused on using mapping programs in programming languages such as FORTRAN or C, but these systems are not very flexible to user required changes in output and input of the mapping program. Others have tried developing a dynamic Manufacturing Execution System (“MES”), but MES do not have all the data and logic required to build a valid fabrication simulation model. The main purpose of an MES is to execute processes to perform the actual manufacturing functions. Additional data and logic must be added to augment the database of the MES.
A system is needed that has the ability to integrate simulation with current data and logic from the MES, to augment gathered parameters with additional data and logic required for a valid customized model, to create scheduling and dispatching orders with a simulation run, and to display the dispatch orders to the manufacturing floor.